Triple
T29754617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quahog 5 News |
E752995
|
entity |
| Predicate | recurringLocationFor |
P26564
|
FINISHED |
| Object | Tom Tucker |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Tom Tucker | Statement: [Quahog 5 News, recurringLocationFor, Tom Tucker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recurringLocationFor Context triple: [Quahog 5 News, recurringLocationFor, Tom Tucker]
-
A.
recurringLocation
chosen
Indicates that an event, action, or state happens repeatedly at the specified location over time.
-
B.
repeatLocation
Indicates that an entity occurs or appears multiple times at the same location or position.
-
C.
recurringEvent
Indicates that an event occurs repeatedly over time according to some regular pattern or schedule.
-
D.
recurringDuring
Indicates that an event or state happens repeatedly within the time span or context defined by another event or interval.
-
E.
recurringSeries
Indicates that an event, action, or pattern occurs repeatedly over time as part of an ongoing series rather than as a one-time instance.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f0d62c84cc8190846f80ae04fdf8ec |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f673c9d2a88190965075607fc73061 |
completed | May 2, 2026, 9:59 p.m. |
| PD | Predicate disambiguation | batch_69f66ac1a4fc81909740d2e52fbe6970 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 7:56 p.m.